Pose normalization of 3D models via reflective symmetry on panoramic views

A novel pose normalization method, based on reflective symmetry computed on panoramic views, is presented. Qualitative and experimental investigation in 3D data-sets has led us to the observation that most objects possess a single plane of symmetry. Our approach is thus guided by this observation. Initially, through an iterative procedure, the symmetry plane of a 3D model is estimated, thus computing the first axis of the model. This is achieved by rotating the 3D model and computing reflective symmetry scores on panoramic view images. The other principal axes of the 3D model are estimated by computing the variance of the 3D model’s panoramic views. The proposed method is incorporated in a hybrid scheme, that serves as the pose normalization method in a state-of-the-art 3D object retrieval system. The effectiveness of this system, using the hybrid pose normalization scheme, is evaluated in terms of retrieval accuracy and the results clearly show improved performance against current approaches.